DocumentCode :
2218394
Title :
Differential evolution with multiple strategies for solving CEC2011 real-world numerical optimization problems
Author :
Elsayed, Saber M. ; Sarker, Ruhul A. ; Essam, Daryl L.
Author_Institution :
Sch. of Eng. & Inf. Technol., Univ. of New South Wales, Canberra, ACT, Australia
fYear :
2011
fDate :
5-8 June 2011
Firstpage :
1041
Lastpage :
1048
Abstract :
Over the last two decades, many Differential Evolution (DE) strategies have been introduced for solving Optimization Problems. Due to the variability of the characteristics in optimization problems, no single DE algorithm performs consistently over a range of problems. In this paper, for a better coverage of problem characteristics, we introduce a DE algorithm framework that uses multiple search operators in each generation. The appropriate mix of the search operators, for any given problem, is determined adaptively. The proposed algorithm has been applied to solve the set of real world numerical optimization problems introduced for a special session of CEC2011.
Keywords :
evolutionary computation; search problems; CEC2011 real-world numerical optimization problems; DE algorithm framework; DE strategy; differential evolution strategy; multiple search operators; multiple strategy; Algorithm design and analysis; Equations; Evolution (biology); Evolutionary computation; Indexes; Mathematical model; Optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation (CEC), 2011 IEEE Congress on
Conference_Location :
New Orleans, LA
ISSN :
Pending
Print_ISBN :
978-1-4244-7834-7
Type :
conf
DOI :
10.1109/CEC.2011.5949732
Filename :
5949732
Link To Document :
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